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2020 – today
- 2024
[j10]Lin Sheng
, Zhenyu Gu, Fangyuan Chang:
A novel integration strategy for uncertain knowledge in group decision-making with artificial opinions: A DSFIT-SOA-DEMATEL approach. Expert Syst. Appl. 243: 122886 (2024)- [j9]Jianan Zhao, Dian Zhu, Fangyuan Chang, Ting Han:
Rehab-Diary: Enhancing Recovery Identity with an Online Support Group for Middle Aged and Older Ovarian Cancer Patients. Proc. ACM Hum. Comput. Interact. 8(MHCI): 1-25 (2024) - [c6]Lin Sheng, Cheng Deng, Junjie Zhang, Fangyuan Chang, Qinghua Sun, Zhenyu Gu:
A Language Model as a Design Assistant for UI Design Recommendation and Evaluation. ECAI 2024: 3821-3827 - [i2]Hongyi Yang, Fangyuan Chang, Dian Zhu, Fumie Muroi, Zhao Liu:
Application of Artificial Intelligence in Schizophrenia Rehabilitation Management: Systematic Literature Review. CoRR abs/2405.10883 (2024) - 2023
- [c5]Fangyuan Chang, Zhenyu Gu, Zhonghao Shi, Wei Tang:
Advancing Cattle Health Monitoring through ACI-Driven Wearable Sensor Technology: A Case Study of Leg-Worn System Development. ACI 2023: 9:1-9:13 - [c4]Van-Hai Bui, Fangyuan Chang, Wencong Su, Mengqi Wang, Yi Lu Murphey, Felipe Leno da Silva, Can Huang, Lingxiao Xue, Ruben Glatt:
Deep Reinforcement Learning-Based Optimal Parameter Design of Power Converters. ICNC 2023: 25-29 - [c3]Zhonghao Shi, Zi'Ang Zhang, Yuanzheng Jia, Jun Li, Xinyue Wang, Yawen Qiu, Jinfeng Miao, Fangyuan Chang, Xiangan Han, Wei Tang:
Internet-of- Things Behavior Monitoring System Based on Wearable Inertial Sensors for Classifying Dairy Cattle Health Using Machine Learning. IICAIET 2023: 277-282 - 2022
- [j8]Van-Hai Bui, Fangyuan Chang, Wencong Su, Mengqi Wang, Yi Lu Murphey, Felipe Leno da Silva, Can Huang, Lingxiao Xue, Ruben Glatt:
Deep Neural Network-Based Surrogate Model for Optimal Component Sizing of Power Converters Using Deep Reinforcement Learning. IEEE Access 10: 78702-78712 (2022) - 2021
- [j7]Fangyuan Chang, Xiaofan Cui, Mengqi Wang, Wencong Su:
Region of Attraction Estimation for DC Microgrids With Constant Power Loads Using Potential Theory. IEEE Trans. Smart Grid 12(5): 3793-3808 (2021) - 2020
- [j6]Fangyuan Chang, Tao Chen, Wencong Su, Qais Alsafasfeh:
Control of battery charging based on reinforcement learning and long short-term memory networks. Comput. Electr. Eng. 85: 106670 (2020) - [j5]Fangyuan Chang, Xiaofan Cui, Mengqi Wang, Wencong Su, Alex Q. Huang:
Large-Signal Stability Criteria in DC Power Grids With Distributed-Controlled Converters and Constant Power Loads. IEEE Trans. Smart Grid 11(6): 5273-5287 (2020) - [c2]Fangyuan Chang, Sanna Kuoppamäki, Britt Östlund:
Integrating Personal Emergency Response Systems (PERS) into Healthcare Professional Practices: A Scoping Review. HCI (28) 2020: 28-46 - [c1]Britt Östlund, Björn Fischer, Barbara Marshall, Nicole K. Dalmer, Mireia Fernández-Ardèvol, Andrea Garcia-Santesmases, Daniel Lopez, Eugène Loos, Fangyuan Chang, Xin Chen, Louis Neven, Alexander Peine, Andrea Rosales, Sanna Kuoppamäki:
Using Academic Work Places to Involve Older People in the Design of Digital Applications. Presentation of a Methodological Framework to Advance Co-design in Later Life. HCI (27) 2020: 45-58 - [i1]Fangyuan Chang, Xiaofan Cui, Mengqi Wang, Wencong Su, Alex Q. Huang:
Large-Signal Stability Criteria in DC Power Grids with Distributed-Controlled Converters and Constant Power Loads. CoRR abs/2005.12373 (2020)
2010 – 2019
- 2019
- [j4]Jie Yuan, Erxia Li, Chaoqun Kang, Fangyuan Chang, Tingting Yuan, Xiaoyong Li:
Latency-Based Dynamic Controller Assignment in Hybrid SDNs: Considering the Impact of Legacy Routers. Future Internet 11(8): 168 (2019) - [j3]Erxia Li, Chaoqun Kang, Deyu Huang, Modi Hu, Fangyuan Chang, Lianjie He, Xiaoyong Li:
Quantitative Model of Attacks on Distribution Automation Systems Based on CVSS and Attack Trees. Inf. 10(8): 251 (2019) - [j2]Jie Yuan, Erxia Li, Chaoqun Kang, Fangyuan Chang, Xiaoyong Li:
Review of the D2D Trusted Cooperative Mechanism in Mobile Edge Computing. Inf. 10(8): 259 (2019) - [j1]Jie Yuan, Erxia Li, Chaoqun Kang, Fangyuan Chang, Xiaoyong Li:
Erratum: Yuan, J. et al. Review of the D2D Trusted Cooperative Mechanism in Mobile Edge Computing. Information 2019, 10, 259. Inf. 10(10): 319 (2019)
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